This factor is based on the view in behavioral finance that "investors under-react to continuous information". The author believes that investors under-react to frequent but small stock price changes with strong continuity, but are more sensitive to a few but significant stock price changes. Therefore, when the cumulative return in the past 12 months is positive (that is, $PRET$ is positive), if the proportion of falling trading days is higher than the proportion of rising trading days (that is, $%neg > %pos$), it means that the market has experienced many small declines during the rise, and the information continuity is strong. Then the value of this factor is negative, and the expected future return will be lower; on the contrary, if the cumulative return in the past 12 months is positive, and the proportion of rising trading days is higher than the proportion of falling trading days, then the value of this factor is positive, and the expected future return will be higher. Conversely, when the cumulative return in the past 12 months is negative, the logic is reversed. Therefore, the higher the factor, the higher the consistency between the direction of the return and the direction of the proportion of rising and falling trading days, and the higher the expected future return. This factor mainly captures the consistency of the return trend and can be used to measure the strength of the momentum effect of the market. It should be noted that this factor does not directly measure momentum, but measures the consistency between the momentum of returns and the continuity of information. The lower the absolute value, the stronger the information continuity, which also indirectly indicates that the market's reaction to stock price changes is weaker, and vice versa.